Model created using AutoGPTQ on a GPT-2 model with 4-bit quantization.
You can load this model with the AutoGPTQ library, installed with the following command:
pip install auto-gptq
You can then download the model from the hub using the following code:
from transformers import AutoModelForCausalLM, AutoTokenizer
from auto_gptq import AutoGPTQForCausalLM, BaseQuantizeConfig
model_name = "mlabonne/gpt2-GPTQ-4bit"
tokenizer = AutoTokenizer.from_pretrained(model_name)
quantize_config = BaseQuantizeConfig.from_pretrained(model_name)
model = AutoGPTQForCausalLM.from_quantized(model_name,
model_basename="gptq_model-4bit-128g",
device="cuda:0",
use_triton=True,
use_safetensors=True,
quantize_config=quantize_config)
This model works with the traditional Text Generation pipeline.
Example of generation with the input text "I have a dream":
I have a dream. I want someone with my face, and what I have. I want to go home. I want to be alive. I want to see my children. I dream if I have the spirit, my body, my voice,
- Downloads last month
- 42
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.